from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HpMatchReporting(other_library="onnx", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time onnx. For instance, a speedup of 2 means that onnx is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.015 | 0.056 | 0.000 | 0.002 | -1 | 1 | 0.676 | 20.115 | 0.082 | 0.676 | 0.100 | 0.100 | See | See |
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.026 | 0.003 | 0.000 | 0.026 | -1 | 1 | 0.000 | 0.360 | 0.009 | 0.000 | 0.072 | 0.072 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.109 | 0.030 | 0.000 | 0.003 | -1 | 5 | 0.743 | 20.016 | 0.025 | 0.743 | 0.155 | 0.155 | See | See |
| 3 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.028 | 0.003 | 0.000 | 0.028 | -1 | 5 | 1.000 | 0.358 | 0.010 | 1.000 | 0.078 | 0.078 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.386 | 0.006 | 0.000 | 0.002 | 1 | 100 | 0.846 | 20.094 | 0.062 | 0.846 | 0.119 | 0.119 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.000 | 0.000 | 0.023 | 1 | 100 | 1.000 | 0.357 | 0.012 | 1.000 | 0.064 | 0.064 | See | See |
| 6 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.136 | 0.052 | 0.000 | 0.003 | -1 | 100 | 0.846 | 20.141 | 0.109 | 0.846 | 0.156 | 0.156 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.026 | 0.003 | 0.000 | 0.026 | -1 | 100 | 1.000 | 0.359 | 0.006 | 1.000 | 0.071 | 0.071 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.348 | 0.011 | 0.000 | 0.002 | 1 | 5 | 0.743 | 19.934 | 0.028 | 0.743 | 0.118 | 0.118 | See | See |
| 9 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.001 | 0.000 | 0.023 | 1 | 5 | 1.000 | 0.347 | 0.005 | 1.000 | 0.065 | 0.065 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.239 | 0.008 | 0.001 | 0.001 | 1 | 1 | 0.676 | 20.424 | 0.038 | 0.676 | 0.061 | 0.061 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.022 | 0.001 | 0.000 | 0.022 | 1 | 1 | 0.000 | 0.346 | 0.005 | 0.000 | 0.063 | 0.063 | See | See |
| 12 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.782 | 0.028 | 0.000 | 0.002 | -1 | 1 | 0.845 | 4.329 | 0.016 | 0.845 | 0.412 | 0.412 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.009 | 0.003 | 0.000 | 0.009 | -1 | 1 | 1.000 | 0.287 | 0.005 | 1.000 | 0.032 | 0.032 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 3.031 | 0.041 | 0.000 | 0.003 | -1 | 5 | 0.883 | 4.249 | 0.011 | 0.883 | 0.713 | 0.713 | See | See |
| 15 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.009 | 0.002 | 0.000 | 0.009 | -1 | 5 | 1.000 | 0.287 | 0.005 | 1.000 | 0.033 | 0.033 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.314 | 0.004 | 0.000 | 0.002 | 1 | 100 | 0.887 | 4.329 | 0.016 | 0.887 | 0.535 | 0.535 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.000 | 0.000 | 0.004 | 1 | 100 | 1.000 | 0.285 | 0.005 | 1.000 | 0.012 | 0.012 | See | See |
| 18 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 3.026 | 0.031 | 0.000 | 0.003 | -1 | 100 | 0.887 | 4.316 | 0.014 | 0.887 | 0.701 | 0.701 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.011 | 0.002 | 0.000 | 0.011 | -1 | 100 | 1.000 | 0.288 | 0.004 | 1.000 | 0.039 | 0.039 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.319 | 0.004 | 0.000 | 0.002 | 1 | 5 | 0.883 | 4.259 | 0.011 | 0.883 | 0.544 | 0.544 | See | See |
| 21 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.000 | 0.000 | 0.004 | 1 | 5 | 1.000 | 0.288 | 0.004 | 1.000 | 0.012 | 0.012 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.096 | 0.003 | 0.000 | 0.001 | 1 | 1 | 0.845 | 4.328 | 0.007 | 0.845 | 0.253 | 0.253 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 1.000 | 0.285 | 0.005 | 1.000 | 0.007 | 0.007 | See | See |
KNeighborsClassifier_kd_tree¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.727 | 0.008 | 0.000 | 0.002 | 1 | 5 | 0.975 | 127.545 | 0.000 | 0.975 | 0.014 | 0.014 | See | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 5 | 1.000 | 3.057 | 0.043 | 1.000 | 0.001 | 0.001 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.944 | 0.017 | 0.000 | 0.001 | -1 | 5 | 0.975 | 128.602 | 0.000 | 0.975 | 0.007 | 0.007 | See | See |
| 3 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.005 | 0.002 | 0.000 | 0.005 | -1 | 5 | 1.000 | 3.050 | 0.041 | 1.000 | 0.001 | 0.001 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.494 | 0.004 | 0.000 | 0.000 | -1 | 1 | 0.964 | 133.698 | 0.000 | 0.964 | 0.004 | 0.004 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 1 | 1.000 | 2.975 | 0.062 | 1.000 | 0.001 | 0.001 | See | See |
| 6 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.806 | 0.005 | 0.000 | 0.001 | 1 | 1 | 0.964 | 135.395 | 0.000 | 0.964 | 0.006 | 0.006 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 1.000 | 2.964 | 0.073 | 1.000 | 0.000 | 0.000 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.153 | 0.021 | 0.000 | 0.005 | 1 | 100 | 0.973 | 132.287 | 0.000 | 0.973 | 0.039 | 0.039 | See | See |
| 9 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | 1 | 100 | 1.000 | 2.959 | 0.048 | 1.000 | 0.001 | 0.001 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.009 | 0.016 | 0.000 | 0.003 | -1 | 100 | 0.973 | 136.798 | 0.000 | 0.973 | 0.022 | 0.022 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.005 | 0.001 | 0.000 | 0.005 | -1 | 100 | 1.000 | 2.989 | 0.079 | 1.000 | 0.002 | 0.002 | See | See |
| 12 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.023 | 0.001 | 0.001 | 0.000 | 1 | 5 | 0.923 | 0.044 | 0.002 | 0.923 | 0.525 | 0.525 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 1.000 | 0.006 | 0.000 | 1.000 | 0.106 | 0.107 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.025 | 0.001 | 0.001 | 0.000 | -1 | 5 | 0.923 | 0.044 | 0.001 | 0.923 | 0.561 | 0.561 | See | See |
| 15 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.005 | 0.004 | 0.000 | 0.005 | -1 | 5 | 1.000 | 0.006 | 0.000 | 1.000 | 0.820 | 0.821 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.024 | 0.001 | 0.001 | 0.000 | -1 | 1 | 0.895 | 0.043 | 0.001 | 0.895 | 0.553 | 0.553 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 1 | 1.000 | 0.006 | 0.000 | 1.000 | 0.391 | 0.391 | See | See |
| 18 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.021 | 0.000 | 0.001 | 0.000 | 1 | 1 | 0.895 | 0.042 | 0.001 | 0.895 | 0.501 | 0.501 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 1.000 | 0.006 | 0.000 | 1.000 | 0.111 | 0.111 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.038 | 0.001 | 0.000 | 0.000 | 1 | 100 | 0.919 | 0.070 | 0.001 | 0.919 | 0.536 | 0.536 | See | See |
| 21 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 1.000 | 0.006 | 0.000 | 1.000 | 0.119 | 0.119 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.037 | 0.001 | 0.000 | 0.000 | -1 | 100 | 0.919 | 0.067 | 0.001 | 0.919 | 0.556 | 0.556 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.001 | 0.000 | 0.002 | -1 | 100 | 1.000 | 0.006 | 0.000 | 1.000 | 0.398 | 0.399 | See | See |
HistGradientBoostingClassifier_best¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: learning_rate=0.01, n_iter_no_change=10.0, max_leaf_nodes=100.0, max_bins=255.0, min_samples_leaf=100.0, max_iter=300.0.
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | HistGradientBoostingClassifier_best | predict | 100000 | 1000 | 100 | 0.130 | 0.002 | 300 | 0.006 | 0.000 | 0.789 | 0.508 | 0.021 | 0.789 | 0.256 | 0.256 | See | See |
| 1 | HistGradientBoostingClassifier_best | predict | 100000 | 1 | 100 | 0.021 | 0.005 | 300 | 0.000 | 0.021 | 1.000 | 0.419 | 0.008 | 1.000 | 0.050 | 0.050 | See | See |